Computer systems have become nearly ubiquitous, ranging from multi-purpose devices such as servers, personal computers, laptop computers and mainframe computers to special purpose devices such as application specific integrated circuits and processors disposed in a wide range of appliances, tools, and other devices. Computers typically take their inputs from a common set of interfaces, including keyboards, mouse devices, microphones, cameras, sensors, and the like. However, while a range of input devices are known for special purpose computers, processing systems for general purpose computers currently focus on two types of inputs: character- and cursor-based inputs from keyboards, mouse devices, touch screens, and the like, and voice-based inputs from microphones (for speech recognition). While there are many applications for those computers, in certain situations it may be difficult for users to provide the necessary inputs. For example, a child or elderly person may not be sophisticated enough to provide the correct keyboard or voice commands, but may be able to make gestures that have recognizable meaning, such as gestures for help. In other situations there may be no available user, making voice- or character-based instructions unavailable. Nevertheless, changes in a given environment may give sufficient visual data to trigger a need for a relevant action (e.g., smoke in a room triggers a need for an alarm). Thus, a need exists for a general purpose processing system that will accept and operate based on image or visual inputs, either alone, or in combination with conventional inputs.
One area in which visual inputs can be used to advantage is face recognition. Face recognition technologies are known in which an image is processed in order to determine whether a face matches one or more reference faces, such as for security purposes. Such technologies may be used, for example, to determine whether a user is permitted entry into a home, office, or similar environment. Current facial recognition approaches, which typically involve comparison of facial features between multiple images and calculations that assess the degree of match, are plagued with problems. One problem is the tendency of such systems to produce false positive matches. A false positive result means that an unauthorized user may be permitted entry into a home, for example. The tendency to produce false positive matches means that users who are seeking to be recognized are typically given only a limited number of attempts to be recognized. However, systems may also produce false negatives; thus, the limitations that are necessary to prevent false positives tend to increase the number of false negatives to the point that legitimate users are denied access in many instances. Thus, a need exists for a system that can limit the instance of false positive matches to an arbitrarily low level, so that a user who wants to be recognized can attempt to be recognized as many times as he or she wishes, without fear that an unauthorized user will be permitted entry.